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A breakdown of my recent personal project! Software used: Blender, Houdini, Liquigen, Gaea, Ae, Ps. Models and tools: Quixel, BigMediumSmall, Polyganiq, Geo-Scatter, Fox Renderfarm, Neat Video Denoiser, Mixamo.

Dylan Donaldson

5,521 subscribers

107,489 次观看 • 2 年前 •via X (Twitter)

科学技术教育

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10 条评论

Dylan Donaldson 的头像

Dylan Donaldson2 年前

Full quality:

ibotpl 的头像

ibotpl2 年前

impressive breakdown!! amazing work, well done.

Dylan Donaldson 的头像

Dylan Donaldson2 年前

🔥 music is 'used2' by @hxly_xo

Jimmy Edward Films 的头像

Jimmy Edward Films2 年前

Zertox… Holy hell phenomenal work brother

Nassos Y 🇵🇸 的头像

Nassos Y 🇵🇸2 年前

This is gorgeous 😍

Dylan Donaldson 的头像

Dylan Donaldson2 年前

Thank you <33

Birchgo 的头像

Birchgo2 年前

This is beautiful!

Dylan Donaldson 的头像

Dylan Donaldson2 年前

Thank you so much!

Caze 的头像

Caze2 年前

amazing!

Dylan Donaldson 的头像

Dylan Donaldson2 年前

Thanks Caze!

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My fox shooting garden defending AI robot is finally done and WORKING! 🤩 (Don’t worry it only shoots 💦 water) After months of slowly moving forward with each part I finished the last step to train a TensorFlow model on the footage of the 🦊 fox I collected hours of footage 📹 with the fox roaming around my garden, from this I labeled around 2000 images with the fox by hand ✋ Honestly, I was quite skeptical training the model was actually gonna work, maybe this was partly the reason I avoided working on this until the very end. If I couldn’t train a model to detect the fox, this whole robot would never be able to function properly. On the flipside though, with no previous experience in hardware or electronics there was a bit of a learning curve and I didn’t want to end up labeling thousands of images, training a TensorFlow model, only to fail on building the hardware. As I started building, I realized that mixing hardware and software adds quite another dimension to debugging things. At times I wasted hours debugging code in my IDE, only to realize the issue was somewhere in the electronics. Furthermore, combining this side project with a full time job and a young family, is not always easy. It can be quite frustrating, to know you only need 4 hours of concentrated effort for a small task, having to spread it out across a week of 20min increments. Then, a few months into the build I noticed the fox had stopped coming to my garden, in fact one day, I recorded her walking with 3 cute little 🐶 pups, and the next day I saw her moving out of my garden completely. Did she know I was building a robot? I had this strange mix of feelings, happy my garden was safe from poop and digging, happy she was safe with her pups, but how was I gonna finish this project if my robot had no fox to detect? For sure they would be back next year, I figured I could postpone the whole thing until next winter, but I also knew it was gonna be much harder to pick up momentum if I did let it sit there for six months. So I decided to keep working, hoping the fox would reappear,.. but she never did. As I finished labeling the footage and started training my model, I could finally see the mAP results, quantifying the precision of my object detection model. It was measuring at 78% across different metrics on detecting my fox. I quickly ran the model on some of the video footage I got from my fox. Inference speed took a hit, but it did a near perfect job detecting the fox, even when she was deep down in the grass or wizzing past in a motion blur. It took me by surprise how well it worked. With the default model I had to drop my confidence threshold way down to 15%, to recognize the fox as 🦜“bird” in one or two frames, with my custom model it followed the fox all the way down to the back of the garden! Still this didn’t solve the issue of there being no actual fox in my garden and how was I gonna wrap this project in a short timeframe. I played with the idea of putting a fox toy 🧸 on an RC 🚗 car, or borrowing a dog to run around the garden to test. Friends suggested I run around the garden in a fox costume.. what a ridiculous idea. I wasn’t really feeling the idea of running around the garden in a floppy cloth fox 🎭 costume, but had a look anyway. I came across these self inflating costumes. This actually could be perfect. Since it’s inflated, it would hold its shape super well, making it much easier to label, train and be recognized by my robot. So I got the costume and shot a time lapse of myself as a fox walking around the garden. I labeled it to around 600 images. Ran the model training again and got a mAP result of 82%. This was even better than my real fox! At this point I knew this was gonna work. So here’s the final 🎥 video, just having some fun with it. I’ll update here whenever the real fox does come back. On a final note, I’m looking for (remote) jobs in these fields of AI now: - object detection - visual generative AI - 3D (nerfs + gaussian splats) So if you know anything let me know! My DMs are open 😊

Jeroen Pixel

55,797 次观看 • 2 年前

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A Fiscal Crisis Is Coming By 2030 And We Have Both Republicans And Democrats To Blame In my recent appearance on Thoughtful Money with our friend Adam Taggart , we unpacked the #math we use to project a US fiscal crisis by 2030 and how both Democrats and the GOP are perpetuating that outcome with socialist policies. If you are still a staunch Democrat or hardcore Republican after watching this, just know that you are dooming our children to a lifetime of slavery. For the rest of you, thanks in advance for ditching the Fox News/Truth Social/MSNBC/CNN propaganda so we can start developing solutions #together. ❤ Please like and repost if you’ve found this PSA helpful. Thank you! P.S. Link to full video:

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123,672 次观看 • 2 年前

Watch Battalion—My First Ever 5-Minute Gen AI Short Film. I had to upload it in two parts. This is part 1; part 2 is in the comments. I created this over a few weeks using 100% image-to-video and text-to-video Generative AI. While not perfect, the tools advance daily, even during production, helping to produce incredible results. This is my most in-depth and longest Gen AI narrative film project. It was created by one person. Watch the full-length 4K pro res here: Various tools helped me bring it to life, and it wouldn't have been possible without the power of AI. The story chronicles the 320th Barrage Balloon Batallion, the only unit to storm the beach during D-Day composed entirely of African American soldiers. They provided critical protection to the ships and soldiers below them from attacks by enemy aircraft. AI tools used: Kling AI Runway Luma Hailuo AI-MiniMax Hub Midjourney Magnific.ai OpenAI Stability AI udio FilmConvert Adobe Premiere Pro Adobe Photoshop Grok Comfyui, Live Portrait

Watch Battalion—My First Ever 5-Minute Gen AI Short Film. I had to upload it in two parts. This is part 1; part 2 is in the comments. I created this over a few weeks using 100% image-to-video and text-to-video Generative AI. While not perfect, the tools advance daily, even during production, helping to produce incredible results. This is my most in-depth and longest Gen AI narrative film project. It was created by one person. Watch the full-length 4K pro res here: Various tools helped me bring it to life, and it wouldn't have been possible without the power of AI. The story chronicles the 320th Barrage Balloon Batallion, the only unit to storm the beach during D-Day composed entirely of African American soldiers. They provided critical protection to the ships and soldiers below them from attacks by enemy aircraft. AI tools used: Kling AI Runway Luma Hailuo AI-MiniMax Hub Midjourney Magnific.ai OpenAI Stability AI udio FilmConvert Adobe Premiere Pro Adobe Photoshop Grok Comfyui, Live Portrait

Dave Clark

273,074 次观看 • 1 年前